Bayesian Optimization by Density Ratio Estimation
Model-based Asynchronous Hyperparameter and Neural Architecture Search
We introduce a model-based method for asynchronous multi-fidelity hyperparameter and neural architecture search that combines the strengths of asynchronous Hyperband and Gaussian …
Aaron Klein
Variational Graph Convolutional Networks
Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference
We derive cycle-consistent adversarial learning (CycleGAN) as a special case of variational inference in a latent-variable model with implicit priors, establishing a Bayesian …